Quinn S Wells | PubMed Health

PubMed2026

Multi-ancestry genetic architecture of heart failure subtypes.

Heart failure (HF) affects 6.7 million people in the US and includes two major subtypes, HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF), with distinct genetic architectures. We meta-analyze genome-wide association studies (GWAS) of 38,781 HFrEF cases, 38,163 HFpEF cases, and 526,135 controls across European, African, Hispanic, and Asian ancestries using the Million Veteran Program and Vanderbilt University DNA Databank (BioVU). We identify 46 genome-wide significant loci for HFrEF (9 novel) and 3 loci for HFpEF (1 novel). Four HFrEF loci are detected in African ancestry participants near CD36, SPI1, TRIM48, and SPNS3, with lead SNPs showing low risk-allele frequencies in European populations. In the all-cause HF meta-analysis (200,070 cases, 2,076,466 controls), we identify 136 loci (12 novel). Gene-based tests, tissue enrichment, transcriptome-wide association, and fine-mapping implicate vascular, metabolic, and TGF-β/Smad signaling pathways and nominate candidate causal genes, clarifying shared and subtype-specific risk across ancestries.

Humans↗

PubMed2026

Prevalence and Clinical Impact of Pathogenic Variants in Cardiomyopathy Genes Among Individuals with Cardiac Conduction Disorders.

IMPORTANCE: Cardiac conduction disorders have traditionally been regarded as a secondary manifestation of underlying structural heart diseases. However, isolated conduction disorders may precede the onset of heart failure (HF) suggesting shared mechanisms. OBJECTIVE: To evaluate the prevalence and clinical significance of pathogenic/likely pathogenic (P/LP) rare variants in cardiomyopathy genes among individuals with conduction disorders. DESIGN SETTING AND PARTICIPANTS: Biobank analysis of 192,834 participants with whole genome sequence data from Vanderbilt's BioVU and 353,092 participants from the All of Us Research Program (AoU). Participants with primary conduction disorder (left bundle branch block [LBBB], right bundle branch block [RBBB], high-grade atrioventricular block [AVB]) were identified after excluding secondary causes. EXPOSURES: P/LP variants in cardiomyopathy genes. MAIN OUTCOMES AND MEASURES: Primary outcome was P/LP carrier status by age and HF status. Secondary outcomes included incident HF and composite ventricular arrhythmias/sudden cardiac death/mortality (VA/SCD/mortality). RESULTS: Among 16,959 participants with conduction disorders in BioVU and 13,442 in AoU, 432 (2.6%) and 206 (1.5%) were P/LP carriers, respectively. Conduction disorder was independently associated with carrier status (BioVU p<0.001; AoU p=0.005). Carrier probability varied by age at conduction disorder onset and HF status. Among participants with HF at age 30 years, predicted carrier probability for LBBB was 7.5% in BioVU and 20.2% in AoU; for high-grade AVB, 7.7% and 8.5%, respectively, compared with 3.7% and 2.9% among those with HF without conduction disorder. P/LP carrier status among participants with conduction disorders was associated with increased risk of incident HF (BioVU p<0.001; AoU p<0.001) and ventricular arrhythmia/sudden death/mortality (BioVU p<0.001; AoU p<0.001). Carriers also demonstrated increased susceptibility to conduction disorder following HF diagnosis, including more than two-fold higher risk of third-degree AVB (BioVU aOR 2.48, 95% CI 1.85-3.32; AoU aOR 2.26, 95% CI 1.35-3.80). CONCLUSIONS: Adults with primary conduction disorders have an increased prevalence of P/LP variants in cardiomyopathy genes, which is most pronounced with diagnoses at early ages of adulthood. Furthermore, there is evidence of an interaction between P/LP carrier status and conduction disorder to increase HF risk and composite cardiovascular outcomes, underscoring the potential role of genetic evaluation in patients with primary conduction disorders to inform long-term outcomes.

Journal Article↗

PubMed2023

Next-generation phenotyping: introducing phecodeX for enhanced discovery research in medical phenomics.

MOTIVATION: Phecodes are widely used and easily adapted phenotypes based on International Classification of Diseases codes. The current version of phecodes (v1.2) was designed primarily to study common/complex diseases diagnosed in adults; however, there are numerous limitations in the codes and their structure. RESULTS: Here, we present phecodeX, an expanded version of phecodes with a revised structure and 1,761 new codes. PhecodeX adds granularity to phenotypes in key disease domains that are under-represented in the current phecode structure-including infectious disease, pregnancy, congenital anomalies, and neonatology-and is a more robust representation of the medical phenome for global use in discovery research. AVAILABILITY AND IMPLEMENTATION: phecodeX is available at https://github.com/PheWAS/phecodeX.

Phenomics↗